530 citations · 2.6k across the 30 of their papers we have counts for
32 papers
Local Conditional Neural Fields for Versatile and Generalizable Large-Scale Reconstructions in Computational Imaging
Hao Wang, Jiabei Zhu, Yunzhe Li +2
Deep learning has transformed computational imaging, but traditional pixel-based representations limit their ability to capture continuous, multiscale details of objects. Here we i…
Roadmap on Deep Learning for Microscopy
Giovanni Volpe, Carolina Wählby, Lei Tian +72
Through digital imaging, microscopy has evolved from primarily being a means for visual observation of life at the micro- and nano-scale, to a quantitative tool with ever-increasin…
Robust single-shot 3D fluorescence imaging in scattering media with a simulator-trained neural network
Jeffrey Alido, Joseph Greene, Yujia Xue +7
Imaging through scattering is a pervasive and difficult problem in many biological applications. The high background and the exponentially attenuated target signals due to scatteri…
Mid-infrared Chemical Imaging of Intracellular Tau Fibrils using Fluorescence-guided Computational Photothermal Microscopy
Jian Zhao, Lulu Jiang, Alex Matlock +6
Amyloid proteins are associated with a broad spectrum of neurodegenerative diseases. However, it remains a grand challenge to extract molecular structure information from intracell…
High-fidelity intensity diffraction tomography with a non-paraxial multiple-scattering model
Jiabei Zhu, Hao Wang, Lei Tian
We propose a novel intensity diffraction tomography (IDT) reconstruction algorithm based on the split-step non-paraxial (SSNP) model for recovering the 3D refractive index (RI) dis…
Deep-learning-augmented Computational Miniature Mesoscope
Yujia Xue, Qianwan Yang, Guorong Hu +2
Fluorescence microscopy is essential to study biological structures and dynamics. However, existing systems suffer from a tradeoff between field-of-view (FOV), resolution, and comp…